Multimetric data fusion-based displacement estimation

Abstract

While displacement is valuable information for the structural behavior, measuring dis-placements from large civil structures is often challenging and costly. Indirect displacement estimation approaches using acceleration or strain have potential to be cost-effective and convenient measurement. The data fusion method is proposed to complementarily make use of acceleration and strain measurement for estimating more accurate displacement so that the problems of existing methods are overcome; the proposed method estimates non-zero mean, dynamic displacements with low-noise. The proposed approach is numerically and experimentally validated, showing better estimation than the single measurement-based methods. To practically realize the proposed method, wireless smart sensor (WSS) was utilized in the study which is, in particular, convenient for measuring multiple measurands. To this end, high-precision strain sensor board compatible with existing acceleration sensor board of WSSs was developed to measure both strain and acceleration. The performance of the proposed approach with WSSs was verified through dynamic response data measured from lab-scale bridge model excited by moving mass; the multiple estimated displacements were compared with laser displacement sensors. The estimated non-zero mean displacement gave sufficient resolution in both time and frequency domain. Full-scale experimental validation was carried out on two types of bridges: a pre-stressed concrete bridge and steel girder bridge. The displacement from the proposed method agrees very well with those from reference devices. Based on the result from experimental validation, the proposed method is then applied to safety monitoring of a railway bridge subjected to 400km/h passage of high-speed train. Three major criteria (i.e., maximum acceleration, maximum deflection and maximum twist) were measured and evaluated; the application to safety monitoring of a railway bridge was successfully vali...